JPS63302317A - Positional speed measuring apparatus of moving object - Google Patents

Abstract

PURPOSE:To enable accurate correction of errors of a global position measuring system (GPS) receiver output, by correcting an output of an inertia reference device by an error vector calculated with a Kalman filter. CONSTITUTION:An inertia reference device 1 is equipped with a gyroscope, a sensor block having an accelerometer and a computer section and outputs signals pertaining to the position, speed and attitude of an airplane. Position and speed signals of the device 1 and a GPS receiver 2 are inputted into a Kalman filter 3. An error correction calculating section 2a calculates an error correction value used as value indicating the degree of a degrading in a position error of the GPS receiver 2 based on a relative relationship between positions of an airplane and a satellite. Then, the Kalman filter 3 generates an error vector based on outputs from the GPS receiver 2 and the error correcting section 2a. Then, a correction section 1a inputs the error vector into a direction cosine matrix updating device, a position calculator and a speed calculator to perform calculations and outputs signals of attitude angle, position and speed with limited errors.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a speed measuring device mounted on a moving object such as an aircraft, a ship, a rocket, or an automobile.

[Conventional technology]

2. Description of the Related Art Conventionally, an inertial reference device is often used as a device for measuring the position, speed, and attitude angle of a moving body. However, the position, velocity, and attitude angle output by the inertial reference device include errors, and in particular, the position error increases as the device operates. Therefore, with the aim of reducing the error included in the output of the inertial reference device and making it a position and speed measuring device with good long-term accuracy, we have developed an inertial reference device and other position and speed measuring devices such as ``fit()'' Tsupura navigation device and Global Positioning System
m (hereinafter referred to as GPS) receiver, etc.).

In this case, as shown in FIG. 6, a method is often used in which an error vector including position error, velocity error, etc. is estimated by Kalman filter calculation, and the error is corrected using this estimation. In this Kalman filter, the difference between the position and speed signal output by the inertial reference device and other positions, the position and speed signal output by the speed measuring device is input as an observation vector, and an error vector is output based on this. ing.

The position and speed signals output by the other position and speed measuring devices mentioned above contain errors, and since these become errors in the observation vector, this error is usually incorporated into the Kalman filter as observation noise. , the average value of the error is used as the value of this observation noise.

[Problem that the invention seeks to solve]

G as another position and velocity measuring device in combination with an inertial reference device
When using a PS receiver and correcting the error using the method shown in Figure 6, the error in the position and speed output by the GPS receiver is determined by the position on the earth of the GPS receiver and the radio wave detected by the GPS receiver. It changes depending on the relative positional relationship with the position of the GPS satellite receiving the signal.

This relative positional relationship changes from time to time due to the movement of the mobile body equipped with the GPS receiver and the movement of the GPS satellite. Therefore, if the value of the observation noise included in the Kalman filter is an average value, the observation error included in the actual observation vector may not match the observation noise included in the Kalman filter, and the estimated error vector accuracy.

may deteriorate. This results in a deterioration in the accuracy of correcting errors in the inertial reference device, leading to a decrease in the performance of the combined device.

The present invention aims to eliminate these conventional drawbacks.

[Means for solving problems]

In order to solve this problem, the present invention uses an inertial reference device that outputs position and speed signals of a moving object, and a G-G system that captures radio waves transmitted from a satellite and outputs position and speed signals of a moving object.
PS=i transmitter receives the output of the inertial reference device and the GPS receiver, and the difference between the two outputs is observed.The observation is performed by a Kalman filter that outputs an error vector that corrects the output of the inertial reference device based on the vector, and the Kalman filter described above. Means for outputting an error correction output of observation noise according to the relative relationship between the position of the moving body detected by the GPS receiver and the position of the satellite is provided.

[Effect]

The error that corrects the output from the inertial reference device is output by a Kalman filter calculation based on the observation vector, which is the difference between the output of the inertial reference device and the output of the GPS receiver. The included observation noise is corrected by an error correction output according to the relative positional relationship between the moving object and the satellite detected by the GPS receiver.

Therefore, errors in the position/velocity signals output by the GPS receiver are accurately corrected according to the position of the moving object.

In this way, by accurately correcting observation noise using the error correction output representing the actual observation error, it is possible to correct errors included in the position and velocity output by the inertial reference device without deteriorating accuracy. is possible.

〔Example〕

An embodiment of the present invention applied to an aircraft will be described with reference to FIGS. 1 to 4. As shown in FIG. 2, the inertial reference device 1 includes a sensor block 11 equipped with a gyro and an accelerometer.
and a computer section 12, which calculates the position n, speed n, and attitude angle 21 of the aircraft based on the detected values of the gyro and accelerometer.
Outputs a signal about .

As shown in Figure 3, a GPS receiver is installed on an aircraft P, and four satellites A, B, C, D,...
・Receive radio waves sent from. The radio waves from the satellite are
It contains data such as time and satellite position, and the GP8 receiver captures this data to measure the three-dimensional position of the aircraft and output position and speed signals.

As shown in FIG. 1, the position and velocity signals of the inertial reference device 1 and the GPS receiver 2 are input to a Kalman filter 3,
In the Kalman filter, the difference between these two signals, H 1ff
The l+vector is calculated and an error vector is output based on this.

Furthermore, in this embodiment, the error correction calculation section 2a uses GPS.
It is provided in the receiver 2. In the calculation unit 2a, for example, GPS data based on the relative relationship between the position of the aircraft and the position of the satellite is calculated.
Error correction (PDOP; Po5ition D) is used as a value representing the degree of deterioration of the receiver position error.
It has a function to calculate the observation error of the GPS receiver caused by the relative relationship between the position of the aircraft and the position of the satellite. That is, as shown in FIG. 4, the time and position (latitude, longitude) of the own aircraft detected by the GPS receiver 2a-1,
2a-2, select the four satellites A, B, C, D and set their Line of Sight.
LO8)-? (BA, +23., (B..

■, get. Next, the transposed matrix (a
, the GPS error covariance 6, which is the error due to the placement, is calculated by the inverse matrix of the product of IH and its transposed matrix E7, with T as matrix elements.Error correction is performed using the diagonal of this GPS error covariance G. This error correction is obtained as the square root of the sum of the squares of the components.This error correction is input to the Kalman filter 3 as an output from the error correction section 2a in FIG. 1, and an error vector is generated. Here, the Kalman filter 3 calculates the Kalman gain IKn and the observation noise IRn while occasionally inputting the open side error correction PDOP according to the flowchart in FIG. Observation vector consisting of difference and speed difference, zn
is input, an error vector 9n (+1) is calculated from the above-mentioned Kalman gain IKn, and this is converted to the inertial reference device [
It is outputted every moment to the correction section 1a of No. 11.

As shown in FIG. 2, this correction unit 1a inputs the above-mentioned error vectors (attitude angle, position, velocity) into the direction cosine matrix updater 1 position calculator and velocity calculator to calculate the error. It outputs small attitude angle 21, position 1f22, and velocity n signals.

This embodiment is configured as described above.

An observation vector that is the difference between the GPS receiver output and the inertial reference device output is input to the Kalman filter 3 by an error correction signal according to the relative positional relationship between the aircraft and the satellite,
An error vector will be output based on the corrected observation noise to correct the output of the inertial reference device.

Therefore, an error correction signal that actually matches the relative relationship between the aircraft position and the satellite position is always input to the Kalman filter, the observation noise is corrected, and the error vector is corrected based on the corrected observation noise. . . . Therefore, it is possible to realize a position and velocity measuring device that always has stable performance in terms of accuracy.

〔Effect of the invention〕

As described above in detail with respect to the embodiments, the present invention can bring about the following effects.

That is, based on the observation vector that is the difference between the GPS receiver output and the inertial reference device output, the Kalman filter calculates the observation noise corrected by an error correction signal according to the relative relationship between the position of the forest moving object and the position of the satellite. Since the output of the inertial reference device is corrected by the error vector calculated based on this, it is possible to accurately correct the error in the GPS receiver output that changes from moment to moment depending on the relative positional relationship between the aircraft and the satellite. Therefore, the accuracy of the position and velocity measuring device can be increased and it can be kept stable at all times.

[Brief explanation of the drawing]

FIG. 1 is an explanatory diagram of an embodiment of the present invention. Fig. 2 is an explanatory diagram of the inertial reference device used in the above embodiment, Fig. 3 is an explanatory diagram of positioning by the GPS receiver used in the above embodiment, and Fig. 4 is an explanation of the error correction calculation section in the above embodiment. FIG. 5 is an explanatory diagram of calculation using a Kalman filter, and FIG. 6 is an explanatory diagram of a conventional position and velocity measuring device. In the drawings, 1 is an inertial reference device, 1a is a correction unit provided in the inertial reference device, 2 is a GPS receiver, 2a is an error correction unit provided in the GPS receiver, and 3 is a Kalman filter. Agent: Patent attorney Akira Sakama and two others (Figure 1 11), 1 (-): Observation change covariance matrix lr;
) n (+>: Observation, measurement tr night rotation matrix IKn
:Kalman gain IFn: State transition matrix of base model Q:W! , system noise of the model jR: observation cone jH: observation, measurement matrix foot; unit matrix Jon(-): base estimate value before observation change n(10):
Estimated error value Zn after observation update; Expressed as the nth value of the first observation. Figure 5 dance? . ! (4)

Claims (1)

[Claims] an inertial reference device that outputs signals of the position and velocity of a moving object;
A global positioning system receiver that captures radio waves transmitted from satellites and outputs signals indicating the position and speed of a moving object, which receives the outputs of the above-mentioned inertial reference device and the global positioning system receiver and calculates the difference between the two outputs. A Kalman filter that outputs an error vector that corrects the output of the inertial reference device based on the observation vector, and observation noise that corresponds to the relative positional relationship between the position of the moving object and the position of the satellite detected by the Global Positioning System receiver. 1. An apparatus for measuring the position and speed of a moving body, comprising means for outputting an error correction output of the above to a Kalman filter.